Nefesh MCP Server

A Model Context Protocol server that gives AI agents real-time awareness of human physiological state — stress level, confidence, and behavioral adaptation prompts.

What it does

Your AI agent sends sensor data (heart rate, voice, video, text) via the Nefesh API. The MCP server returns a unified stress score (0–100), a state label (Calm → Acute Stress), and an adaptation prompt that tells the agent how to adjust its behavior.

Signals supported: cardiovascular (HR, HRV, RR intervals), vocal (pitch, jitter, shimmer), visual (facial action units), textual (sentiment, keywords)

Setup

1. Get an API key

Get your key at nefesh.ai/pricing ($25/month, 50,000 calls).

2. Add to your AI agent

Find your agent's MCP config file:

Agent	Config file
Cursor	~/.cursor/mcp.json
Windsurf	~/.codeium/windsurf/mcp_config.json
Claude Desktop	~/Library/Application Support/Claude/claude_desktop_config.json
Claude Code	.mcp.json (project root)
VS Code (Copilot)	.vscode/mcp.json or ~/Library/Application Support/Code/User/mcp.json
Cline	cline_mcp_settings.json (via UI: "Configure MCP Servers")
Continue.dev	.continue/config.yaml
Roo Code	.roo/mcp.json
Amazon Q	~/.aws/amazonq/mcp.json
JetBrains IDEs	Settings → Tools → MCP Server
Zed	~/.config/zed/settings.json (uses context_servers)
OpenAI Codex CLI	~/.codex/config.toml
Goose CLI	~/.config/goose/config.yaml
ChatGPT Desktop	Settings → Apps → Add MCP Server (UI)
Gemini CLI	Settings (UI)
Augment	Settings Panel (UI)
Replit	Integrations Page (web UI)
LibreChat	librechat.yaml (self-hosted)

Add the following configuration (works with most agents):

{
  "mcpServers": {
    "nefesh": {
      "url": "https://mcp.nefesh.ai/mcp",
      "headers": {
        "X-Nefesh-Key": "<YOUR_API_KEY>"
      }
    }
  }
}

<details> <summary><strong>VS Code (Copilot)</strong> — uses <code>servers</code> instead of <code>mcpServers</code></summary>

{
  "servers": {
    "nefesh": {
      "type": "http",
      "url": "https://mcp.nefesh.ai/mcp",
      "headers": {
        "X-Nefesh-Key": "<YOUR_API_KEY>"
      }
    }
  }
}

</details>

<details> <summary><strong>Zed</strong> — uses <code>context_servers</code> in settings.json</summary>

{
  "context_servers": {
    "nefesh": {
      "settings": {
        "url": "https://mcp.nefesh.ai/mcp",
        "headers": {
          "X-Nefesh-Key": "<YOUR_API_KEY>"
        }
      }
    }
  }
}

</details>

<details> <summary><strong>OpenAI Codex CLI</strong> — uses TOML in <code>~/.codex/config.toml</code></summary>

[mcp_servers.nefesh]
url = "https://mcp.nefesh.ai/mcp"

</details>

<details> <summary><strong>Continue.dev</strong> — uses YAML in <code>.continue/config.yaml</code></summary>

mcpServers:
  - name: nefesh
    type: streamable-http
    url: https://mcp.nefesh.ai/mcp

</details>

All agents connect via Streamable HTTP — no local installation required.

Tools

Tool	Description
ingest_signal	Send raw sensor data. Returns unified stress score + state + adaptation prompt.
get_state	Get current physiological state for a session.
get_history	Get state history over time for a session.
delete_subject	GDPR-compliant deletion of all data for a subject.

Quick test

After adding the config, ask your AI agent:

"What tools do you have from Nefesh?"

It should list the tools above.

State labels

Score	State
0–19	Calm
20–39	Relaxed
40–59	Focused
60–79	Stressed
80–100	Acute Stress

Documentation

• Quick Start
• API Reference
• State Mapping

Privacy

• No video uploads — edge processing runs client-side
• No PII stored — strict schema validation
• GDPR/BIPA compliant — cascading deletion via delete_subject
• Not a medical device — for contextual AI adaptation only

License

Proprietary. See nefesh.ai/terms.